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The interactive electrode localization utility: software for automatic sorting and labeling of intracranial subdural
Roan A LaPlante1,2, Wei Tang3, Noam Peled4,5
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. aestrivex@gmail.com.
International Journal of Computer Assisted Radiology and Surgery
|December 5, 2016
Summary
A new open-source software simplifies the process of sorting, labeling, and localizing intracranial electroencephalography (iEEG) electrodes. This tool automates tasks previously requiring manual inspection, achieving 96% accuracy in electrode identification.
Area of Science:
- Neurosurgery
- Medical Imaging
- Computational Neuroscience
Background:
- Intracranial electroencephalography (iEEG) electrode placement requires precise localization.
- Current methods for iEEG electrode analysis often involve time-consuming manual image inspection.
Purpose of the Study:
- To introduce an open-source software package for the automated registration, localization, and labeling of iEEG electrodes.
- To develop a method for automatic sorting and labeling of electrodes from subdural grids.
Main Methods:
- Developed an interactive electrode localization utility integrating CT and MR image analysis.
- Implemented an algorithm for automatic sorting and labeling of subdural grid electrodes.
Main Results:
- The software pipeline was validated in twelve subjects undergoing iEEG monitoring.
- The automated sorting and labeling algorithm demonstrated 96% accuracy in electrode identification.
Conclusions:
- The developed software significantly simplifies the workflow for iEEG electrode analysis.
- The automated methods offer high performance, reducing the need for manual inspection in clinical practice.
